Mastering Logistic Regression with Categorical Predictors: Always Positive Odds Ratios (4K)

Enjoy! 🥳

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[juanfederos]

I have to agree - beautiful as always! Always happy to see an new video by you!

[lorcangray]

Your video's are great, explaining things very clearly, and making my journey learning data science much simpler! thank you. Also, are you planning on doing a video for GLMs?

[lorenzoplaserrano]

again again and again, awesome video, I would love to learn from you directly

[ibrahimlawan]

Excellent and educating.
Thank you.
We now don't have access to the details of your tutorial on the website!

[CrickBritney]

Thank you for this amazing video. Can you please do a video of confounding correction using regression and using the residuals for downstream analysis such as PCA, Vocalno plot, and t.test.

[aram]

Thank you for video! How can we flip the levels in gtsummary as you did in emmeans? To have a >1 odds ratios in your example: 1st/3rd. I mean choose the reference level.

[joshstat]

Since you've been covering the use of emmeans in some of your videos, apparently, how about you will discuss the use of contrast constants? On the other hand, I am recently creating an R package that will also covers it (base R's usage or other packages' usages are somewhat clunky) and I will really make it sure that your "design" is more readable and "fast".

[OnLyhereAlone]

Thanks again for a beautiful presentation.
One question: Since odds ratio scale may be very large, and I want to present the final plot as probabilities instead (to have the predictable 0 to 1 scale), is it correct to use the pairwise comparison inferences and p values (based on odds ratios) to show the contrasts between pairs of the probabilities in my final plot?
Thank you.

[nguyentho]

Can you make video about path analysis process?

[heymantpanthi]

thank you for the video, can i still use emmeans in multinominal logit model ? and i have a mix of continuous and categorical variables as my independent variables